add new interface

app.py

@@ -2,6 +2,32 @@ import gradio as gr
 from lettucedetect.models.inference import HallucinationDetector
 import os
 
+
+title = """# 🙋🏻‍♂️Welcome to 🌟Tonic's 🥬 LettuceDetect - 🤯🧠 Hallucination Tester 🟢🔴"""
+description= """
+        Powered by `lettucedect-large-modernbert-en-v1` from KRLabsOrg. Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!
+        
+        ### How to Use:
+        1. Enter a **Context** (source document or info).
+        2. Enter a **Question** related to the context.
+        3. Enter an **Answer** to evaluate.
+        4. Press **Submit** to see if the answer hallucinates!
+        
+        - 🟢 = No hallucinations
+        - 🔴 = Hallucinations detected
+        - Highlighted text shows hallucinated spans in **red** with confidence scores.
+"""
+join_us = """
+## Join us:
+🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 
+[![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/n8ytYeh25n) 
+On 🤗Huggingface: [MultiTransformer](https://huggingface.co/MultiTransformer) 
+On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [Data Tonic](https://github.com/multiTonic/thinking-dataset/)
+🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
+"""
+
+
+
 # Initialize the LettuceDetect model
 detector = HallucinationDetector(
     method="transformer", 
@@ -68,26 +94,14 @@ def evaluate_hallucination(context, question, answer):
 
 # Gradio Blocks interface
 with gr.Blocks(
-    title="🥬 LettuceDetect Hallucination Tester 🟢🔴",
-    theme="ParityError/Anime"
+    title="🥬 LettuceDetect Hallucination Tester 🟢🔴"
 ) as demo:
-    gr.Markdown(
-        """
-        # 🥬 LettuceDetect Hallucination Tester 🟢🔴
-        Powered by `lettucedect-large-modernbert-en-v1` from KRLabsOrg. Detect hallucinations in answers based on context and questions using ModernBERT with 8192-token context support!
-        
-        ### How to Use:
-        1. Enter a **Context** (source document or info).
-        2. Enter a **Question** related to the context.
-        3. Enter an **Answer** to evaluate.
-        4. Press **Submit** to see if the answer hallucinates!
-        
-        - 🟢 = No hallucinations
-        - 🔴 = Hallucinations detected
-        - Highlighted text shows hallucinated spans in **red** with confidence scores.
-        """
-    )
-    
+    gr.Markdown(title)
+    with gr.Row():
+        with gr.Group():
+            gr.Markdown(description)
+        with gr.Group():
+            gr.Markdown(join_us)
     with gr.Row():
         with gr.Column(scale=2):
             # Inputs
@@ -108,12 +122,15 @@ with gr.Blocks(
             submit_btn = gr.Button("Submit")
         
         with gr.Column(scale=3):
-            # Outputs
-            status_output = gr.Label(label="Status")
-            explanation_output = gr.Textbox(label="Explanation", interactive=False)
+            with gr.Row():
+                with gr.Column():
+                    status_output = gr.Label(label="Status")
+                with gr.Column():
+                    explanation_output = gr.Textbox(label="Explanation", interactive=False)
+
             highlighted_answer_output = gr.HighlightedText(
                 label="Answer with Hallucinations Highlighted",
-                show_legend=True,
+                show_legend=False,
                 color_map={"hallucination": "red"},  # Note: Only "hallucination" is used as base category
                 combine_adjacent=True
             )